• 제목/요약/키워드: 전자상거래 성과

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A Study on Privacy Influencing the Continuous Intention to Use in Closed-Type SNS: Focusing on BAND Users (폐쇄형 SNS에서 프라이버시가 지속적인 사용의도에 미치는 영향에 관한 연구: 밴드 사용자를 중심으로)

  • Lim, Byungha;Kang, Dongwon
    • Information Systems Review
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    • v.16 no.3
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    • pp.191-214
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    • 2014
  • In this study, based on Privacy Calculus Model, we study whether users' intention of continuous use of closed-type SNS is affected by information privacy concern. In addition, we propose a model that studies if the major factors of the intention of continuous use which are trust, satisfaction and benefits could control the information privacy concern's effect on the intention of use. As a result, companies have to consider protecting the psychological privacy and information privacy of the individual when they design SNS.

A Study on the RFID Biometrics System Based on Hippocampal Learning Algorithm Using NMF and LDA Mixture Feature Extraction (NMF와 LDA 혼합 특징추출을 이용한 해마 학습기반 RFID 생체 인증 시스템에 관한 연구)

  • Oh Sun-Moon;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.4 s.310
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    • pp.46-54
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    • 2006
  • Recently, the important of a personal identification is increasing according to expansion using each on-line commercial transaction and personal ID-card. Although a personal ID-card embedded RFID(Radio Frequency Identification) tag is gradually increased, the way for a person's identification is deficiency. So we need automatic methods. Because RFID tag is vary small storage capacity of memory, it needs effective feature extraction method to store personal biometrics information. We need new recognition method to compare each feature. In this paper, we studied the face verification system using Hippocampal neuron modeling algorithm which can remodel the hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature vector of the face images very fast. and construct the optimized feature each image. The system is composed of two parts mainly. One is feature extraction using NMF(Non-negative Matrix Factorization) and LDA(Linear Discriminants Analysis) mixture algorithm and the other is hippocampal neuron modeling and recognition simulation experiments confirm the each recognition rate, that are face changes, pose changes and low-level quality image. The results of experiments, we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to the existing method.

A Quantitative Trust Model based on Empirical Outcome Distributions and Satisfaction Degree (경험적 확률분포와 만족도에 기반한 정량적 신뢰 모델)

  • Kim, Hak-Joon;Sohn, Bong-Ki;Lee, Seung-Joo
    • The KIPS Transactions:PartB
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    • v.13B no.7 s.110
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    • pp.633-642
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    • 2006
  • In the Internet environment many interactions between many users and unknown users take place and it is usually rare to have the trust information about others. Due to the lack of trust information, entities have to take some risks in transactions with others. In this perspective, it is crucial for the entities to be equipped with functionality to accumulate and manage the trust information on other entities in order to reduce risks and uncertainty in their transactions. This paper is concerned with a quantitative computational trust model which takes into account multiple evaluation criteria and uses the recommendation from others in order to get the trust for an entity. In the proposed trust model, the trust for an entity is defined as the expectation for the entity to yield satisfactory outcomes in the given situation. Once an interaction has been made with an entity, it is assumed that outcomes are observed with respect to evaluation criteria. When the trust information is needed, the satisfaction degree, which is the probability to generate satisfactory outcomes for each evaluation criterion, is computed based on the empirical outcome outcome distributions and the entity's preference degrees on the outcomes. Then, the satisfaction degrees for evaluation criteria are aggregated into a trust value. At that time, the reputation information is also incorporated into the trust value. This paper also shows that the model could help the entities effectively choose other entities for transactions with some experiments in e-commerce.

Analysis on Targeting Countries for Overseas Expansion of Korean Companies: Focusing on The Difference between Shipping, Manufacturing and Logistics Companies (우리나라 기업의 해외진출 대상 국가에 관한 연구: 제조·물류 기업별 차이를 중심으로)

  • Kim, Sang Youl;Park, Ho;Jang, Hyunmi;Kim, Taehun
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.3087-3099
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    • 2018
  • Due to the constant changes of companies' global networks, the expansion of global e-commerce as well as the market-oriented global supply chain management, global enterprises are strategically selecting and entering into viable countries able to become global footholds. Therefore, this study aims to scrutinize the trend of changes in the global networks of Korean companies by analyzing the current overseas countries over the past decade. From the analysis, it has been found that there is a significant difference in the priorities of targeting countries among shipping, manufacturing and logistics companies. Logistics companies preferred to enter Germany first while they attached to a lower priority to Singapore. Manufacturing companies had a lower priority to advance to India, while they preferred to advance to Mexico; however, shipping companies were analyzed to prefer to enter the US. In addition, all of these companies identified the importance of securing volume and network by entering overseas markets to achieve economies of scale and scope and to maintain global competitiveness. Joint overseas expansion of manufacturers with shipping and logistics companies can be recommended to facilitate the entry and thus, enhance global competitiveness and service capabilities and also secure new growth engines.

E-commerce Food Purchases by Adult Women according to their Household Types (가구 형태별 성인 여성의 전자상거래 식품 구매 실태)

  • Park, Yu-Jin;Kim, Yu-Mi;Choi, Mi-Kyeong
    • Korean Journal of Community Nutrition
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    • v.25 no.6
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    • pp.464-473
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    • 2020
  • Objectives: The purpose of this study was to compare and analyze e-commerce food purchase behavior and the perceptions of adult women according to their household types. Methods: The e-commerce food purchases of 318 adult women were surveyed and analyzed according to their household types (one-person or couple household (OCH); a household with children (HC); a household with parents (HP)). Results: The total amount of food purchases over 6 months through e-commerce according to household types was in the descending order of OCH (60.3%), HC (57%), and HP (55.1%) thus showing a significant difference (P < 0.05) in behavior between household types. The reasons for purchasing food through e-commerce included: a lower price than offline (30.8%), convenient delivery and transportation (30.2%), and food diversity (21.1%). When purchasing food online, the most important factor was price and quality, followed by quick and accurate delivery for OCH, exact information given about the product for HC, and recommendation from other consumers for HP (P < 0.01). The main foods purchased through e-commerce were coffee, tea (42.1%), instant and frozen foods (39.9%), water, beverages, dairy products (37.7%), snacks, bread, rice cakes (31.5%), and functional foods (27.4%). The percentage of respondents who were very satisfied or satisfied with their e-commerce food purchases was HP (84.1%), OCH (69.9%), and HC (65.6%) in that order (P < 0.05), and 96.5% of all subjects stated that they would be willing to purchase food through e-commerce in the future. The advantages of purchasing food through e-commerce were seen to be the highest in order and payment convenience with 4.1 points out of 5, followed by low price (4.0), variety of products (3.9), and ease of food purchase (3.9). Among the disadvantages listed, concerns about product damage and deterioration during delivery and differences between the displayed product and the delivered product were the highest with 3.7 points. Conclusions: The characteristics and perceptions of female consumers according to household types are important factors in enhancing the reach of e-commerce, and in preparing guidelines for food selection through e-commerce.

Implementaion Mechanism of Homepage Failure Notification System in Public Sector in IDC Environment (IDC환경에서 공공부문 홈페이지 장애상황공지 시스템 구축방안)

  • Kim, Yong-Tae;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.426-433
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    • 2021
  • Investment in public sector information services has been on the rise in recent years. The supply of high-speed Internet and smartphones has become more common, and the stability of the information system provided to the public in the public sector has become an important management factor. In other words, tasks such as handling civil complaints and issuing certificates by public institutions, financial transactions by banks, customs clearance work, and e-commerce by individuals or institutions are mostly done online. Therefore, how to deal with obstacles arising from the information system, which is in charge of important civil service affairs, is becoming a very important issue. In other words, in the case of a disability that does not function normally even for a short period of time, various problems can occur when the work is delayed, as well as causing serious financial damage to the civil petitioner. This could be accompanied by a decline in public confidence and various other damages such as filing civil complaints. The reasons for the occurrence of information system failures are very diverse and realistically difficult to predict when. Among the various measures to cope with disability, this paper proposed a plan to establish a disability situation notification system that can minimize confusion caused by disability in the event of a homepage malfunction. The proposed disability situation notification system was established in the public IDC environment to show the possibility of utilization.

A Study on the New Freight Charging Model for Parcel Service (택배서비스의 새로운 택배요금 모델에 관한 연구)

  • Song, Young-sim;Park, Hyun-Sung
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.135-144
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    • 2021
  • In Korea, the parcel delivery service is showing a high growth rate every year thanks to the activation of e-commerce, but the courier unit price continues to drop. Due to the low cost of parcel delivery, there is a need for improvement to normalize courier rates due to deterioration in profitability for couriers, deterioration in service for consumers, and overwork and accidents for workers. In this study, a rational rate system model and a systematic approach were presented. The study method modeled the chargeable weight by reflecting the voulumatirc weight and revenue ton by the volume and weight of the cargo, and presented a new parcel freight charge model based on the cost of delivery. In addition, a rate-determining support system was developed that can be easily, conveniently and reasonably determined on-site. In the demonstration, the rate difference was determined by relying on weight rather than volume, and 63.5% for personal courier and 40% for B2C courier were found to be inadequate. This study could be used as an alternative to solving side effects and problems at the delivery site, in the urgent need for research on ways to improve delivery prices.

A Fuzzy-AHP-based Movie Recommendation System using the GRU Language Model (GRU 언어 모델을 이용한 Fuzzy-AHP 기반 영화 추천 시스템)

  • Oh, Jae-Taek;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.19 no.8
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    • pp.319-325
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    • 2021
  • With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

A Study on the Enhancing Recommendation Performance Using the Linguistic Factor of Online Review based on Deep Learning Technique (딥러닝 기반 온라인 리뷰의 언어학적 특성을 활용한 추천 시스템 성능 향상에 관한 연구)

  • Dongsoo Jang;Qinglong Li;Jaekyeong Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.41-63
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    • 2023
  • As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

An Analysis of Success Factors in Internet Shopping Malls (인터넷 쇼핑몰구축의 성공요인에 대한 분석)

  • 진영배;권영식
    • Journal of the Korea Computer Industry Society
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    • v.2 no.12
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    • pp.1495-1504
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    • 2001
  • The main purpose of this research is to show Internet shopping mall the strategic way with the analysis of success factors in Internet shopping malls. To achieve the above purpose, the success factors and variables were defined by the survey of the reference. Sample malls for the research un selected of shopping malls registered in yahoo, Lycos, Empas and Hanmir regardless of their type and class, and did an online-survey of their operation. From the above method, the following results are deduced. First, there are five factors in the success of Internet shopping malls: the effectiveness of customer management the effectiveness of marketing. the competitiveness of product-sales, the convenience of use, the credibility of product. Second, the effectiveness of marketing is positively related to the number of member, visitors, and sales. Third, the credibility of product is negatively related to the number of member, visitors, and sales. At the end, the number of member and visitor are positively related to sales. This result could provide the managers with highly relevant managerial issues. The implication of the study are discussed and futher research directions are proposed.

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